基于高光谱特征的雅氏落叶松尺蠖虫口密度估算  

Estimation of the population density of Erannis jacobsoni(Lepidoptera:Geometridae)based on hyperspectral features

作　　者：白力嘎 黄晓君[1,2,3] Ganbat DASHZEBEGD Mungunkhuyag ARIUNAAD Tsagaantsooj NANZADD Altanchimeg DORJSUREN 包刚 佟斯琴[1,2] 包玉海[1,2] 银山 Enkhnasan DAVAADORJ[5] BAI Li-Ga;HUANG Xiao-Jun;Ganbat DASHZEBEGD;Mungunkhuyag ARIUNAAD;Tsagaantsooj NANZADD;Altanchimeg DORJSUREN;BAO Gang;TONG Si-Qin;BAO Yu-Hai;YIN Shan;Enkhnasan DAVAADORJ(College of Geographical Science, Inner Mongolia Normal University, Huhhot 010022,China;Inner Mongolia Key Laboratory of Remote Sensing & Geography Information System, Huhhot 010022, China;Inner Mongolia Key Laboratory of Disaster and Ecological Security on the Mongolia Plateau, Huhhot 010022, China;Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulan Bator 15170, Mongolia;Institute of General and Experimental Biology, Mongolian Academy of Sciences, Ulan Bator 13330, Mongolia)

机构地区：[1]内蒙古师范大学地理科学学院,呼和浩特010022 [2]内蒙古自治区遥感与地理信息系统重点实验室,呼和浩特010022 [3]内蒙古自治区蒙古高原灾害与生态安全重点实验室,呼和浩特010022 [4]蒙古国科学院地理与地质研究所,蒙古国乌兰巴托15170 [5]蒙古国科学院综合实验生物学研究所,蒙古国乌兰巴托13330

出　　处：《昆虫学报》2021年第6期711-721,共11页Acta Entomologica Sinica

基　　金：国家自然科学基金项目(41861056,61631011);内蒙古自然科学基金项目(2018MS04008);内蒙古科技计划项目(2021GG0183);内蒙古师范大学引进高层次人才科研启动经费项目(2020YJRC051)。

摘　　要：【目的】多年来,蒙古高原典型落叶松害虫雅氏落叶松尺蠖Eeannis jacobsoni发生频繁,使森林生态系统遭到严重破坏。虫口密度可直接描述森林虫害严重程度,进而及时、快速获得害虫虫口密度信息显得极为重要。本研究旨在依据雅氏落叶松尺蠖暴发区的落叶松光谱实测数据和虫口密度数据,构建基于高光谱特征的虫口密度估算方法。【方法】以蒙古国后杭爱省和肯特省4个地点雅氏落叶松尺蠖暴发区为试验区。首先从这4个试验区选取不同程度受害的110株西伯利亚落叶松Larix sibirica样本树,调查虫口密度和测量冠层光谱反射率;其次通过光谱反射率数据获得微分光谱反射率(differential spectral reflectance,DSR)和计算改进型光谱指数(modified spectral index,MSI);再次运用多项式曲线拟合法,分析DSR和MSI对虫口密度的敏感性;然后借助连续投影算法(successive projection algorithm,SPA)提取敏感DSR和MSI;最后利用敏感DSR和MSI,结合多项式回归(polynomial regression,PR)和支持向量机回归(support vector machine regression,SVMR)算法,建立雅氏落叶松尺蠖虫口密度估算模型,并评定了其精度。【结果】DSR的敏感波段主要在黄边和红边波段内,其中572 nm的敏感性最显著(R2=0.5821,P<0.001),MSI的最敏感指数为TVI(R2=0.5386,P<0.001);TVI(R2CV=0.6323,RMSECV=0.1513)比DSR572(R2CV=0.5581,RMSECV=0.1649)估算精度高,而多个DSR(R2=0.7309,RMSECV=0.1347)比多个MSI(R2CV=0.6537,RMSECV=0.1453)更有估算潜力,其中SVMR模型性能始终优于PR模型,说明SVMR更加适用于虫口密度估算。【结论】MSI和DSR可作为虫口密度估算的敏感指标,多项式曲线拟合法能够挖掘MSI和DSR对虫口密度的敏感性;SPA是虫口密度敏感光谱特征提取的一种有效方法,其提取的DSR敏感指标和MSI敏感指数充分捕捉了针叶叶绿素吸收特征、水分吸收特征以及针叶细胞受损引起的反射特征。该研究不仅为利用【Aim】Over the years,the typical larch pest of the Mongolian Plateau,Erannis jacobsoni,has occurred frequently,and caused severe damage to forest ecosystem.Population density can directly describe the severity of forest pests,and it is extremely important to obtain information on pest population density in a timely and rapid manner.The purpose of this study is to construct a population density estimation method based on the hyperspectral data of larch trees and the population density data of E.jacobsoni in the outbreak areas of E.jacobsoni.【Methods】Outbreak areas of E.jacobsoni in four localities in Hangay Province and Khentiy Province in Mongolia were selected as the test areas.Firstly,from the four test areas 110 sample trees of Siberian larch(Larix sibirica)with different degrees of damage were selected,and the population density and the spectral reflectance of the canopy was measured.Secondly,the differential spectral reflectance(DSR)and the modified spectral index(MSI)were calculated through spectral reflectance data.Thirdly,the polynomial curve fitting method was used to analyze the sensitivity of DSR and MSI to population density.Then,the successive projection algorithm(SPA)was used to extract sensitive DSR and MSI.Finally,the sensitive DSR and MSI,polynomial regression(PR)and support vector machine regression(SVMR)algorithms were used to establish the population density estimation model of E.jacobsoni,and the accuracy was evaluated.【Results】The sensitive bands of DSR are mainly in the yellow edge and red edge,and the sensitivity at 572 nm was the most significant(R2=0.5821,P<0.001).The most sensitive index of MSI was TVI(R2=0.5386,P<0.001).The TVI(R2CV=0.6323,RMSECV=0.1513)was more accurate than DSR572(R2CV=0.5581,RMSECV=0.1649),while multiple DSRs(R2CV=0.7309,RMSECV=0.1347)had higher estimation potential than multiple MSIs(R2CV=0.6537,RMSECV=0.1453),and the performance of its SVMR model was always better than the PR model,suggesting that SVMR is suitable for population density estimation.【Co

关 键 词：雅氏落叶松尺蠖 落叶松 虫口密度 改进型光谱指数 微分光谱反射率 估算模型 

分 类 号：O968[理学]